Update app.py

app.py

@@ -1,59 +1,253 @@
+"""Haqeeqat Check — Gradio interface for Hugging Face Spaces.
+
+Run locally:  python app.py
+"""
+
 import os
+import subprocess
 import sys
+from pathlib import Path
 
-from .config import debug_enabled
-from .verdict_agent import VerdictAgent
+# ---------------------------------------------------------------------------
+# Ensure GROQ_API_KEY is loaded from Space secrets before any module import
+# ---------------------------------------------------------------------------
+if not os.environ.get("GROQ_API_KEY"):
+    pass  # will be read at runtime by verification/config.py
 
+import gradio as gr
+
+try:
+    import spaces
+    _HAS_SPACES = True
+except ImportError:
+    _HAS_SPACES = False
+
+# ---------------------------------------------------------------------------
+# Model bootstrap — runs once at import time
+# ---------------------------------------------------------------------------
+_MODEL_FILES = ["best_norm_ED.pth", "yolov8m_UrduDoc.pt"]
+
+
+def _ensure_models():
+    """Download OCR + Whisper models if not already present."""
+    root = Path(__file__).resolve().parent
+    models_dir = root / "models"
+    if os.environ.get("SPACE_ID"):
+        models_dir = Path("/home/user/app/models")
+    if all((models_dir / name).is_file() for name in _MODEL_FILES):
+        return
+    subprocess.run(
+        [sys.executable, str(root / "download_models.py")],
+        check=True,
+    )
 
-def main(argv=None, ingestor=None, agent=None):
-    argv = list(sys.argv if argv is None else argv)
-    debug = "--debug" in argv
-    argv = [arg for arg in argv if arg != "--debug"]
-    if debug:
-        os.environ["HAQEEQAT_DEBUG"] = "1"
-    if len(argv) != 2:
-        print(
-            "Usage: python -m verification.app [--debug] <image|audio|video file>",
-            file=sys.stderr,
-        )
-        return 2
-    path = argv[1]
 
-    if ingestor is None:
+_ensure_models()
+
+# ---------------------------------------------------------------------------
+# Lazy singletons — heavy imports deferred until first request
+# ---------------------------------------------------------------------------
+_ingestor = None
+_agent = None
+
+
+def _get_ingestor():
+    global _ingestor
+    if _ingestor is None:
         from ingestion.ingestor import HaqeeqatIngestor
+        _ingestor = HaqeeqatIngestor()
+    return _ingestor
+
+
+def _get_agent():
+    global _agent
+    if _agent is None:
+        from verification.verdict_agent import VerdictAgent
+        _agent = VerdictAgent()
+    return _agent
+
+
+# ---------------------------------------------------------------------------
+# Labels
+# ---------------------------------------------------------------------------
+URDU_LABELS = {"sacha": "سچا", "jhoota": "جھوٹا", "mashkook": "مشکوک"}
+ENGLISH_LABELS = {"sacha": "True", "jhoota": "False", "mashkook": "Unverified"}
+VERDICT_ICONS = {"sacha": "✔", "jhoota": "✗", "mashkook": "?"}
+
+
+# ---------------------------------------------------------------------------
+# Core processing
+# ---------------------------------------------------------------------------
+
+if _HAS_SPACES:
+    @spaces.GPU
+    def _gpu_startup():
+        """Dummy function so Gradio 6.x detects a GPU-capable handler at startup."""
+        pass
+
+
+def _resolve_path(file_data) -> str | None:
+    """Extract a filesystem path from a Gradio FileData object or plain string."""
+    if isinstance(file_data, str):
+        return file_data
+    # Gradio 6.x FileData: object with .path or dict-like access
+    if hasattr(file_data, "path"):
+        return file_data.path
+    if isinstance(file_data, dict):
+        return file_data.get("path")
+    return None
+
+
+def _process_media_inner(file_data) -> tuple[str, str]:
+    """Ingest a media file, verify claims, return (verdict_box, reasoning_box)."""
+    if file_data is None:
+        return "کوئی فائل منتخب نہیں / No file selected.", ""
+
+    # Gradio 6.x passes a FileData object; extract the path string
+    file_path = _resolve_path(file_data)
+    if not file_path:
+        return "کوئی فائل منتخب نہیں / No file selected.", ""
+
+    ingestor = _get_ingestor()
+    agent = _get_agent()
+
+    report = ingestor.ingest(file_path)
+    text = report.get("combined_text", "")
+    if not text or not text.strip():
+        return "کوئی متن نکالا نہیں جا سکا / No text was extracted from the file.", ""
+
+    if report.get("metadata", {}).get("ocr_garbled"):
+        return (
+            "تصحیح OCR ناکام رہی / OCR failed to read this image properly.\n"
+            "براہ کرم واضح تصویر اپ لوڈ کریں / Please upload a clearer image."
+        ), f"استخراج شدہ متن:\n{text[:300]}"
 
-        ingestor = HaqeeqatIngestor()
-    if agent is None:
-        agent = VerdictAgent()
+    result = agent.run(text)
+
+    if not result.is_checkworthy:
+        return "کوئی قابلِ تصدیق دعویٰ نہیں / No checkworthy claim found.", (
+            f"استخراج شدہ متن:\n{text[:500]}"
+        )
 
-    report = ingestor.ingest(path)
-    text = report["combined_text"]
-    if not text.strip():
-        print("No text could be extracted from the file.", file=sys.stderr)
-        return 1
+    verdict_box = _format_verdict(result)
+    reasoning_box = _format_reasoning(result)
+    return verdict_box, reasoning_box
 
+
+def _process_text(text: str) -> tuple[str, str]:
+    """Verify a pasted text claim, return (verdict_box, reasoning_box)."""
+    if not text or not text.strip():
+        return "براہ کرم متن لکھیں / Please enter some text.", ""
+
+    agent = _get_agent()
     result = agent.run(text)
-    if debug_enabled():
-        print(f"DEBUG extracted_text: {text!r}")
-        print(f"DEBUG claim_urdu: {result.claim_urdu}")
-        print(f"DEBUG claim_english: {result.claim_english}")
-        print(f"DEBUG verdict: {result.verdict.value if result.verdict else None}")
-        print(f"DEBUG confidence: {result.confidence:.2f}")
-        print(f"DEBUG evidence_count: {len(result.evidence)}")
-        for i, item in enumerate(result.evidence):
-            print(f"DEBUG evidence[{i}]: {item.source_domain} | {item.title} | {item.url}")
+
     if not result.is_checkworthy:
-        print("کوئی قابلِ تصدیق دعویٰ نہیں")
-        return 0
+        return "کوئی قابلِ تصدیق دعویٰ نہیں / No checkworthy claim found.", ""
+
+    verdict_box = _format_verdict(result)
+    reasoning_box = _format_reasoning(result)
+    return verdict_box, reasoning_box
+
+
+# Wrap _process_media_inner with @spaces.GPU on HF so UTRNet gets a GPU.
+if _HAS_SPACES:
+    @spaces.GPU
+    def _process_media(file_data) -> tuple[str, str]:
+        return _process_media_inner(file_data)
+else:
+    _process_media = _process_media_inner
+
+
+def _format_verdict(result) -> str:
+    key = result.verdict.value
+    icon = VERDICT_ICONS[key]
+    urdu_label = URDU_LABELS[key]
+    eng_label = ENGLISH_LABELS[key]
+    lines = [
+        f"{icon}  فیصلہ / Verdict:  {urdu_label} ({eng_label})",
+        f" Confidence: {result.confidence:.0%}",
+        "",
+        f"دعویٰ / Claim:",
+        f"  {result.claim_urdu}",
+        f"  {result.claim_english}",
+    ]
+    return "\n".join(lines)
+
+
+def _format_reasoning(result) -> str:
+    parts = [
+        "وجوہات / Reasoning:",
+        "",
+        result.reasoning_urdu,
+        "",
+        result.reasoning_english,
+    ]
+    if result.evidence:
+        parts.append("")
+        parts.append("شواہد / Sources:")
+        for item in result.evidence:
+            parts.append(f"  [{item.source_domain}] {item.title}")
+            parts.append(f"  {item.url}")
+            if item.snippet:
+                parts.append(f"  {item.snippet[:200]}")
+            parts.append("")
+    return "\n".join(parts)
+
+
+# ---------------------------------------------------------------------------
+# Gradio UI
+# ---------------------------------------------------------------------------
+def build_ui() -> gr.Blocks:
+    with gr.Blocks(
+        title="Haqeeqat Check — Urdu Misinformation Detector",
+    ) as demo:
+        gr.Markdown(
+            "# Uraan Techathon 2.0\n"
+            "# Haqeeqat Check: Urdu Misinformation Detector\n"
+            "### حقیقت چیک: اردو غلط معلومات کی جانچ پڑتال"
+        )
+
+        with gr.Tabs():
+            with gr.Tab("Image"):
+                img_input = gr.Image(label="تصویر اپ لوڈ کریں / Upload Image", type="filepath")
+                img_btn = gr.Button("Check / چیک کریں", variant="primary")
+
+            with gr.Tab("Audio"):
+                aud_input = gr.Audio(label="آڈیو اپ لوڈ کریں / Upload Audio", type="filepath")
+                aud_btn = gr.Button("Check / چیک کریں", variant="primary")
+
+            with gr.Tab("Video"):
+                vid_input = gr.Video(label="ویڈیو اپ لوڈ کریں / Upload Video")
+                vid_btn = gr.Button("Check / چیک کریں", variant="primary")
+
+            with gr.Tab("Paste Text"):
+                txt_input = gr.Textbox(
+                    label="اردو متن لکھیں یا پیسٹ کریں / Enter or paste Urdu text",
+                    lines=5,
+                )
+                txt_btn = gr.Button("Check / چیک کریں", variant="primary")
+
+        gr.Markdown("---")
+        verdict_output = gr.Textbox(
+            label="فیصلہ / Verdict",
+            lines=8,
+            interactive=False,
+        )
+        reasoning_output = gr.Textbox(
+            label="وجوہات و شواہد / Reasoning & Sources",
+            lines=14,
+            interactive=False,
+        )
+
+        img_btn.click(fn=_process_media, inputs=img_input, outputs=[verdict_output, reasoning_output])
+        aud_btn.click(fn=_process_media, inputs=aud_input, outputs=[verdict_output, reasoning_output])
+        vid_btn.click(fn=_process_media, inputs=vid_input, outputs=[verdict_output, reasoning_output])
+        txt_btn.click(fn=_process_text, inputs=txt_input, outputs=[verdict_output, reasoning_output])
 
-    print(f"دعویٰ: {result.claim_urdu}")
-    print(f"فیصلہ: {result.verdict_label_urdu} (confidence {result.confidence:.2f})")
-    print(f"وجوہات: {result.reasoning_urdu}")
-    print("ذرائع:")
-    for item in result.evidence[:3]:
-        print(f"  - {item.title} ({item.url})")
-    return 0
+    return demo
 
 
 if __name__ == "__main__":
-    raise SystemExit(main())
+    demo = build_ui()
+    demo.launch(theme=gr.themes.Soft())